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Automatic Control and Computer Sciences
Erschienen in: Automatic Control and Computer Sciences 6/2018

01.11.2018

Methodology of Effective Task Planning and Algorithm for Multivariate Computation of the Characteristics of a Quantum Rotation Sensor on a Hybrid Supercomputer Cluster

verfasst von: A. S. Ilyashenko, S. P. Voskoboynikov, S. M. Ustinov, A. A. Lukashin

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 6/2018

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Abstract

The problem of planning supercomputer computations is considered using the example of computing the characteristics of a quantum rotation sensor model. A methodology for applying the task scheduling algorithm is proposed. For this purpose, time estimates were obtained for computations at cluster nodes. The possibility of dividing settlements by cluster nodes without additional synchronization costs is shown. A start-up algorithm for improving the efficiency of multivariate computations is presented, and the efficiency of the planning algorithm in its use is estimated.
Vorheriger Artikel Theoretical Design of Band Pass Filter Utilizing Long Period Fiber Grating Having Cladding Refractive Index Perturbation
Nächster Artikel Design of New Fractional Sliding Mode Control Due to Complete Synchronization of Commensurate and Incommensurate Fractional Order Chaotic Systems
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Ilyashenko, A.S., Lukashin, Al.A., Zaborovsky, V.S., and Lukashin, An.A., Algorithms for planning resource-intensive computing tasks in a hybrid supercomputer environment for simulating the characteristics of a quantum rotation sensor and performing engineering calculations, Autom. Control Comput. Sci., 2017, vol. 51, no. 6, pp. 426–434.CrossRef
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Metadaten
Titel
Methodology of Effective Task Planning and Algorithm for Multivariate Computation of the Characteristics of a Quantum Rotation Sensor on a Hybrid Supercomputer Cluster
verfasst von
A. S. Ilyashenko
S. P. Voskoboynikov
S. M. Ustinov
A. A. Lukashin
Publikationsdatum
01.11.2018
Verlag
Pleiades Publishing
Erschienen in
Automatic Control and Computer Sciences / Ausgabe 6/2018
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI
https://doi.org/10.3103/S014641161806007X

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